Sharon Freshour is a PhD candidate in the Human and Statistical Genetics program at Washington University in St. Louis. She graduated from St. Edward’s University in 2016 with a B.S. in Mathematics. She is interested in utilizing next generation sequencing and bioinformatic analysis to understand the genomic landscape of cancer and how it relates to treatment response. Her current research topics include using whole genome sequencing to explore copy number alterations in childhood brain tumors and using single cell RNA sequencing to understand mechanisms of response to checkpoint inhibitor treatment in a mouse model of bladder cancer.
Sharon Freshour, Bryan Fisk, Christopher Miller, Joshua Rubin, Obi L. Griffith, Malachi Griffith
Washington University School of Medicine, St. Louis, MO, USA
Brain and central nervous system tumors are the most common form of solid tumor cancers and the second most common cancer overall among children. Although advances have been made in understanding the genomics of childhood brain tumors, the role of copy number alterations (CNAs) has not been fully characterized. While genomes of childhood brain tumor patients are generally considered to be relatively stable diploid genomes, analysis of a subset of pretreatment diagnostic samples from a cohort of 84 deceased patients with a variety of brain cancer diagnoses from Washington University revealed widespread alterations, suggesting CNAs may play a larger role in childhood brain tumors than originally thought. Low-pass whole genome sequencing of these samples showed that 75 out 84 patients had detectable presence of CNAs (Percentage genome altered (total altered bp/3.2?10^9 bp)?100%: mean 16%, median 7%, range 0-50%). Preliminary results examining correlations between the percentage of the genome that was copy number altered and event free or overall survival indicated that CNA percentage may have prognostic value. To explore these results further, 200 additional samples from the Pediatric Brain Tumor Atlas curated by The Children’s Brain Tumor Network were analyzed, revealing similar trends in copy number alteration. Additionally, alterations that were recurrently detected across samples were identified and similar analyses were performed to determine whether certain alterations or patterns of alteration could be predictive of event free or overall survival. 219 alterations were identified as significantly recurrently mutated and of these, 22 alterations were associated with changes in overall survival.